Policy Research Working Paper 6164

Job Creation through Infrastructure Investment in the Middle East

and North AfricaElena Ianchovichina

Antonio Estache Renaud Foucart Grégoire Garsous

Tito Yepes

The World BankMiddle East and North Africa RegionOffice of the Chief EconomistAugust 2012

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Produced by the Research Support Team

Abstract

The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

Policy Research Working Paper 6164

In the next 10 years or so, the infrastructure sector has the potential to generate significant employment. This paper estimates annual job creation of about 2.0 million in direct jobs and 2.5 million in direct, indirect and induced infrastructure-related jobs just by meeting the infrastructure investment needs of about 6.9 percent of gross domestic product (about US$106 billion) for the Middle East and North Africa region on average. The breakdown in expected needs is 11 percent in developing oil exporters, 6 percent in oil importing countries, and 5 percent in the Gulf Cooperation Council oil exporters. Needs are particularly high in electricity and roads. While important, infrastructure job creation will not resolve the region’s unemployment problem

This paper is a product of the Office of the Chief Economist, Middle East and North Africa Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at eianchovichina@worldbank.org.

alone and its job creation potential varies greatly across countries. Moreover, the current ability to finance and hence meet the infrastructure needs varies significantly across countries. Oil importers are likely to fall short under business as usual scenarios. In a region in which the public sector is the main source of infrastructure financing, fiscal choices will thus matter to job creation through infrastructure. But there are more challenges, including the governance of job creation, and the proper targeting and costing of subsidies for job creation and the (re)training programs needed. Managing expectations will also matter, as infrastructure jobs will help but will not solve the region’s unemployment and underemployment problems.

Job creation through infrastructure investment in the Middle East and North Africa

Elena Ianchovichina, Antonio Estache, Renaud Foucart, Grégoire Garsous and Tito Yepes1

JEL: H54, J21

Key words: infrastructure, investment, employment, job creation

Sector Board: EPOL

1 Elena Ianchovichina is Lead Economist at the Chief Economist Office of the World Bank’s Middle East and North

Africa region. Estache, Foucart and Garsous are with the Université Libre de Bruxelles and the European Center for

Advanced Research in Economics and Statistics (ECARES), Brussels, Belgium. Yepes is with Fedesarollo, Bogota,

Colombia. The authors are grateful to Caroline Freund, Jonathan Walters, Ilhem Salamon, Robert Bacon, and many other

colleagues at the World Bank. Any mistake is ours and should not be blamed on any of the organizations we are affiliated

with. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not

necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its

affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

2

1. Introduction

Lack of job opportunities, especially for young people, is a well known, major issue in the

Middle East and North Africa (MENA).2 The region’s labor force has been growing at a rapid

pace – a consequence of relatively high population growth and rising female labor force

participation, but job creation has been lagging behind. The need to achieve tangible

employment results relatively quickly has become urgent in the context of the Arab Spring

events. This paper assesses the potential for job creation through infrastructure investment in the

MENA region in an environment in which heightened regional and global uncertainty has

temporarily restrained private investment - the traditional source of new jobs in expanding

economies.

Because effectively directed and fostered, infrastructure investment has a deep and far

reaching impact on economic development, it is often also seen as a potential quick source of

jobs. Moreover, it can potentially be designed to help meet social goals. Indeed, improved

provision of high-quality basic infrastructure services, such as hospitals, schools, and water

supply and sanitation, raises living standards, improves employability of populations and

prospects for inclusive growth.

MENA has, in fact, done quite well in using public investment to stimulate growth and

jobs, including in infrastructure. For the last 25 years, public investment spending in MENA was

higher than in most developing regions (except East Asia) and twice as large as the OECD

average, largely because of robust spending in the oil exporting countries which benefited from

rising fuel prices. Spending on infrastructure boosted employment in the construction sector,

which was a major source of job growth in the 2000s relative to both other sectors and other

countries. Construction created about 30% of the jobs in MENA, which was twice the average

for fast growing, high investment countries such as Indonesia and Brazil.

The paper shows that maintaining and spreading the momentum in infrastructure will be

important to support growth and job creation in the Middle East and North Africa. To do so,

policymakers will have to recognize that there are large differences in the initial conditions

across the region in terms of stocks, needs, fiscal commitments, private sector participation

potential and job creation potential.

The paper is organized as follows. Section 2 explains the sector context and Section 3 the

sub-regional context. Section 4 summarizes the data available on the current level of

employment in MENA’s infrastructure sector. Section 5 discusses the main methods used to

assess the job creation potential of the infrastructure sector and explains how we do it for the

MENA region. Section 6 concludes with policy recommendations.

2 For ease of exposition and analysis, throughout the paper we use the following country classification for the

Middle East and North Africa. The region is composed of three non-overlapping sub-regions: GCC oil exporters,

developing oil exporters and oil importers. The GCC oil exporters consist of Bahrain, Kuwait, Oman, Qatar, Saudi

Arabia, and the United Arab Emirates (UAE). The developing oil exporters, also referred to in the paper as other oil

exporters, include Algeria, Islamic Republic of Iran, Iraq, Libya, Syria, and Yemen. The oil importers are Egypt,

Tunisia, Morocco, Lebanon, Jordan, Djibouti and West Bank and Gaza. Developing MENA is used to refer to the

group of developing oil exporters and oil importers.

3

2. Sector context

While infrastructure investment in the region overall has been strong (Table 1), there is wide

variation across countries in the quality and quantity of infrastructure (Table 2). The high-income

Gulf Cooperation Council (GCC) group has the best infrastructure endowments and services in

the region, reflecting advanced stage of development and commitment to infrastructure

investments financed by oil revenues. However, infrastructure deficiencies in developing MENA

remain a concern.

Table 1: Infrastructure endowments in the developing world (averages 2005-2008)

Sector EAP ECA LAC MENA SA SSA

Density of paved road network 1,128 1,051 2,965 2,179 467 1,095

km / 1,000 km2 of arable land

Telephone Density

400 929 839 537 353 273

Fixed and mobile subscribers per

1,000 people

Electricity generating capacity 0.30 0.92 0.44 0.30 0.31 0.11

Million KWh per million people

Access to electricity 62 NA 86 91 48 31

% of population with access

Improved Water 81 94 91 88 82 67

% of population with access

Improved Sanitation 62 90 78 83 55 33

% of population with access

Source: World Bank Development Indicators

Table 2: Infrastructure endowments in MENA by country grouping (averages 2005-2008)

Sector OIC OEC GCC Density of paved road network

3,220 618 16,907 Km / 1,000 km2 of arable land

Telephone Density

535 538 1,351

Fixed and mobile subscribers per

1,000 people

Electricity generating capacity 0.3 0.4 2.9

Million KWh per million people

Access to electricity 98 85 98

% of population with access

Improved Water 93 79 97

% of population with access

Improved Sanitation 84 81 99

% of population with access

Source: World Bank Development Indicators

The infrastructure gap challenge is particularly important for oil importing countries

(OIC). In these countries, public investment spending has been following a downward trend and

continues to be weak simply because they have much more limited fiscal space than the oil

exporters (Figure 1). Growth in public-private partnerships had recently been helping to close the

gap in some oil importing countries, but the economic consequences of the Arab uprisings,

combined with economic difficulties in Europe, have reduced private investment, with possible

negative consequences for infrastructure spending.

4

Figure 1. Fiscal space indicators

Data sources: World Bank, IMF and Government sources.

Differences in the quality and quantity of infrastructure endowments and services across

countries as well as differences in needs within countries and sectors make the identification of

infrastructure needs quite complex in the region. Moreover, under a business as usual scenario,

the gaps are likely to magnify as demand for infrastructure grows with population and income

growth, and countries face challenges related to water and energy conservation, efficiency, and

climate change.

When little detailed data are available to conduct a bottom-up approach, the assessment of

infrastructure needs can be based on the estimation of econometric models of demand for each

infrastructure subsector. Fay and Yepes (2003) and Yepes (2008) are among the best known

papers illustrating the method across regions of the world. In this paper, we improve their earlier

estimates for the MENA region by: (i) including data on infrastructure stocks for countries of the

region from national sources as compared to relying on extrapolations from international

databases; (ii) updating the data from original international sources; and (iii) including high

income countries (GCC) in the definition of MENA. Demand for infrastructure is assessed by

regressing per capita stocks of infrastructure against per capita income, the share of GDP derived

from agriculture and manufactures, population growth and density, urbanization rate, and

technology (Table 3).

-20

-10

0

10

20

30

40

50

60

70

80

2008 2010 2008 2011 2008 2011f 2008 2011f

Government debt as % of GDP

External debt (% of GDP)

Gross official reserves, in

months of imports

Fiscal balance as % of GDP

GCC countries

Developing oil exporters

Oil importers

5

Table 3. Econometric Models of Infrastructure Needs

Projected levels of infrastructure stocks are valued at the unit costs used in Yepes (2008)

and shown in Table 4. Time dummies and country fixed effects are used in order to proxy

differences in infrastructure prices. In the case of telecommunications and ports, a market age

variable accounts for the speed of technological change across countries. Lagged dependant

variables are included to eliminate the structural part of interest. Analysis of spurious regressions

have been made as in the literature showing that a structure of lagged variables as in Arellano

and Bond estimations can eliminate all variance thus eliminating the structural part of interest

(Yepes, Pierce and Foster, 2008).

The models are estimated on a worldwide dataset, although with a partial coverage of

regions including MENA. The database used for these estimations is an annual panel data of

infrastructure stocks, macroeconomic variables, and demographic characteristics (see for details

the data annex). Data for MENA countries covers years up to 2008. The data are taken mainly

from the World Bank’s World Development Indicators (WDI) complemented with material from

Paved

Roads

Total

Roads Rails Ports

Telephone

mainlines

Mobile

lines

Electricity

generation

Method

Probit for

grouped

data

Fixed

Effects

Fixed

Effects

Fixed

Effects

Logit for

grouped

data

Logit for

grouped

data

Fixed

Effects

Per capita GDP

-0.261*** 0.111* -0.0107 1.124*** 0.983*** 0.414*** 0.652***

(0.00188) (0.0575) (0.0422) (0.164) (0.000166) (0.000175) (0.0549)

Share of manufactures

in GDP

0.131*** 0.00209 -0.0428 0.152 0.0686*** -0.142*** 0.199***

(0.00183) (0.0435) (0.0395) (0.111) (0.000178) (0.000197) (0.0343)

Share of agriculture in

GDP

-0.179*** -0.0772 0.0630 -0.202* 0.199*** 0.184*** 0.147***

(0.00197) (0.0491) (0.0393) (0.121) (0.000153) (0.000186) (0.0429)

Population density

-0.574*** -0.427*** -0.929*** 0.409 -0.00914*** 2.133*** -0.00847

(0.00459) (0.116) (0.102) (0.298) (0.000294) (0.000354) (0.100)

Urbanization

-0.493*** 0.377*** -0.0421 0.279 3.361*** 1.259*** 0.141

(0.00541) (0.137) (0.112) (0.337) (0.000515) (0.000530) (0.0872)

Population growth

-1.645*** -0.828***

(0.00133) (0.00157)

Time trend

0.0985*** -5.684 -1.224 0.0697***

(0.000500) (4.146) (1.304) (0.0126)

Time trend squared

0.00714 0.00155

(0.00519) (0.00164)

Market age

0.102*** 0.107*** 0.111***

(0.0121) (1.37e-05) (1.69e-05)

Market age squared

-0.00117*** -0.00366*** 0.00414***

(0.000235) (3.78e-07) (5.67e-07)

Constant

-35.32*** 1,128 236.2 -15.28*** -8.373*** -13.74*** -34.94***

(0.191) (828.6) (260.0) (2.094) (0.00281) (0.00287) (4.722)

Observations A 633 551 496 a a 1,034

R-squared 0.119 0.540 0.801 0.459

Number of coefficients 172 109 102 173 Notes: Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1. All relevant variables are in logarithms. a indicates a

large number of observations due to the grouped technique.

6

country official statistical offices and other multilateral organizations (see Annex).3 The annual

GDP growth rate for the world as a whole is assumed to be 3.5% per year in the period 2011-

2020, while that for MENA is 4.3%. Oil importing countries are assumed to grow at 3.5% per

year, while developing oil exporters and GCC countries are assumed to grow at 4.6% and 4.5%,

respectively.4 Demographic trends are taken from the 2009 UN Urbanization Prospects.

Table 4: Unit costs of infrastructure by sector (US$)

Sector Cost per unit Unit Depreciation rate (%)

Electricity generation 2,000 kW 4

Paved roads 410,000 Kilometer 4.7

Unpaved roads 50,000 Kilometer 7.2

Rails 900,000 Kilometer 4

Rural water and sanitation 150 person 3

Urban sanitation 150 person 3

Rural sanitation 130 person 3

Urban water 80 person 3

Main telephone lines* 127-580 line 8

Mobile lines* 127-451 line 8

Access to electricity 195 person 4

Ports 348 TEU 4

Wastewater treatment 120 person 3

Source: Yepes (2008). *Varies by region.

In order to assess the full budgetary allocation needed by the various sectors, estimates of

the associated maintenance needs are included as well. Maintenance is needed for any

investment to meet its assumed lifetime so a commitment to maintenance is built into the cost-

benefit analysis and the calculation of the social rate of return of the investments. In this paper,

maintenance costs are estimated by multiplying the stock value in the previous period by a

depreciation rate. A fixed annual depreciation rate is assumed for each sector and shown in

Table 4. Estimates of total annual expenditure needs by sector, sub-group and region are

presented in Table 5. In the absence of data for a sector or subsector in a country, regional

averages of investment were imputed to obtain total investment needs.5

3 In some cases recent trends of annual growth of the same series are used to fill in missing values. United Nations

National Accounts Main Aggregates Database is used for historical GDP and for the value added components of

agriculture and manufacturing. Additional data on container port traffic is taken from the Containerization

International Yearbook (1970-2006). Extra information on roads and paved roads is available for Oman. GDP

projections are from the World Bank. 4 When past growth rates were not available, a Hodrick-Prescott filter (with a smoothing factor of 100) was used to

obtain the long-run growth rate trend of the past ten years (1999-2009) resulting in an implied annual growth rate

equivalent to that of the World Bank projections. Growth rates are then used to obtain 2010-2020 GDP scenarios. 5 Regional averages of investment as a share of GDP were used in the following cases: roads in Syria, electricity in

West Bank and Gaza, water and sanitation in Bahrain, sanitation in Saudi Arabia and Ports in Bahrain, Iraq, Libya,

Qatar, Syria and West Bank and Gaza.

7

Table 5. Annual expenditure needs for infrastructure in the MENA region

Sector OIC OEC GCC TOTAL

Percent of GDP

Transport 2.2 5.1 2.0 3.0

Paved Roads 1.4 2.7 0.6 1.4

Unpaved Roads 0.6 2.1 1.3 1.4

Rails 0.1 0.1 0.0 0.1

Ports 0.1 0.1 0.1 0.1

ICT 0.8 1.1 0.2 0.6

Telephone mainlines 0.2 0.3 0.0 0.2

Mobile lines 0.6 0.7 0.2 0.4

Electricity 2.5 4.2 2.5 3.0

Electricity generation 2.1 3.7 2.4 2.7

Electricity Access 0.4 0.5 0.1 0.3

Water and Sanitation 0.5 0.6 0.1 0.3

Water 0.2 0.2 0.0 0.13

Sanitation 0.3 0.3 0.1 0.19

Total needs 6.0 10.9 4.8 6.9

Total financing 4.3 12.2 8.3 8.8

Amount (in 2005 US$ million)

Transport 8,575 22,492 14,453 45,519

Paved Roads 5,448 12,088 3,956 21,492

Unpaved Roads 2,246 9,497 9,461 21,204

Rails 428 639 75 1,143

Ports 452 268 960 1,680

ICT 3,021 4,707 1,559 9,287

Telephone mainlines 696 1,464 259 2,419

Mobile lines 2,325 3,243 1,300 6,868

Electricity 9,894 18,607 17,602 46,103

Electricity generation 8,214 16,467 17,139 41,820

Electricity Access 1,680 2,140 463 4,283

Water and Sanitation 1,764 2,497 647 4,908

Water 745 1,040 190 1,975

Sanitation 1,019 1,458 457 2,934

TOTAL 23,254 48,303 34,261 105,818

Share by country group 22% 46% 32% 100%

Investment 10,261 20,739 15,786 46,786

Maintenance 12,992 27,564 18,475 59,032

Source: Authors’ calculations. Note: Total financing is estimated based on IMF/IFS investment data and World Bank

Private Participation Infrastructure database.

8

3. Sub-regional context

The overall infrastructure and maintenance needs are quite large and assessed at about 106

billion dollars per year or 6.9% of the annual regional GDP through 2020. The estimated

differences in needs across sub-regions are just as impressive. Developing oil exporting countries

(OEC) are expected to have to commit almost 11% of their GDP annually ($48 billion) on

improving and maintaining their national infrastructure endowments, while the oil importing

countries (OIC) and the GCC oil exporters will need approximately 6% and 5% of their GDP,

respectively, to ensure enough infrastructure to meet their growth and poverty reduction targets.

Investment and rehabilitation needs are likely to be especially high in the electricity and

transport sectors, particularly roads. Electricity and transport are each estimated to account for

about 43% of total infrastructure needs in MENA, followed by ICT (9%) and water and

sanitation (5%). Fulfilling the electricity need alone would require approximately 3% of the

annual, regional GDP or $46 billion, of which 10 billion will be spent in oil importing countries,

and around 36 billion in the oil exporting countries. During the next decade developing oil

importers in MENA will need to spend about $86 billion dollars on upgrading their transport

networks, while the developing and GCC oil exporters will need $225 billion and $145 billion,

respectively. Rehabilitation needs are expected to account for slightly more than half of total

infrastructure needs.

While oil exporters will be able to meet their national infrastructure needs if they

maintain investment spending at rates prevailing in the 2000s, oil importers will fall short. Since

the vast majority of funding for infrastructure comes from public budgets, it will be critical to

protect public investment budgets and try to increase resources going to the sector in the case of

oil importers. Doing so will be a smart choice for governments looking to create jobs and

growth. The fiscal challenge will be the toughest for the poorest countries of the region since

they are the least likely to be able to attract private financing for infrastructures required to meet

population’s needs.

4. Current infrastructure employment

A comparison of employment shares by sector and country to international benchmarks provides

a first-round assessment of the extent to which infrastructure activities could play a role in

speeding up job creation in MENA. The shares are computed using ILO data that disaggregate

employment into industrial sectors at the 1-digit ISIC level allowing an identification of

electricity and water sector jobs as well as jobs in transport and communications. Data on

construction is included as an important element of infrastructure investment. The construction

category encompasses housing and building construction. These two activities are likely to be the

main drivers of job creation, but other infrastructure investments are still likely to account for a

significant share of employment creation.

Table 6 shows that MENA’s infrastructure sectors, including construction and

infrastructure services, employ close to one-fifth of the regional workforce, or 18.2 million

people. About 11 million workers are employed in construction while the remaining 7.5 million

provide infrastructure services. Within infrastructure services, the transport and communication

sectors are the biggest employers, representing jointly about 7% of total employment, while

workers employed in energy and water represent approximately 1%. These aggregate numbers

9

hide significant variation across countries, as Iran for example employs more than 40% of the

country’s workforce in the construction and infrastructure sectors, while Egypt and Yemen

employ just around 11%.

Table 6 Employment shares by sector

(% of all employed in 2009)

Source: ILO

Developing oil exporting countries have a higher share of jobs in the infrastructure and

construction sectors, not only relative to other groups in the region, but also relative to

international benchmarks. In contrast, oil importers’ employment shares are more in line with

international averages, although their employment in infrastructure is below various international

benchmarks (Table 6). It is worth noting that many of the infrastructure and construction jobs in

the GCC economies are performed by migrant workers, although lack of data precludes

separating out the impact of infrastructure investments on employment of migrant and national

workers.

Assuming that world benchmarks gauge the normal size of employment in the

infrastructure sector (Table 6), we conclude that in general the scope for increasing the relative

size of employment in the sector is limited. The same is the case for employment in construction

in all sub-regions and the region as a whole, although there is some scope to expand the relative

Total Construction Infrastructure

GCC oil exporters 18 12 6

UAE 19 13 6

Saudi Arabia 18 7 11

Qatar 18 10 8

Oman 21 11 10

Kuwait 19 13 6

Bahrain 18 15 3

Developing oil exporters 23 13 10

Yemen 11 7 5

Iraq 15 9 6

Iran 42 37 5

Algeria 15 9 6

Syria 15 8 7

Oil importers 17 9 7

Tunisia 16 11 5

WB&G 23 15 8

Morocco 25 14 11

Jordan 21 13 8

Egypt 11 3 8

MENA 19 11 8

World Average 16 8 8

Developed countries 15 8 7

Developing countries 16 9 8

10

size of employment in infrastructure services in oil importing and GCC countries where

infrastructure’s employment share is below world norms.

5. Assessing the employment effects of infrastructure investment in MENA

This section distinguishes between direct and indirect jobs as well as between short term and

long term effects. These differences have important policy and political dimensions as discussed

below.

Short-term employment effects

The short-term employment generated by infrastructure spending is typically assessed in

two steps. First, direct employment is estimated using information on the nature of infrastructure

spending and the amount of different types of labor required by financed projects. Second,

indirect and induced employment effects are estimated using multipliers from past experience

that link these types of employment to direct employment. In order to estimate how much direct

employment a given investment project would create, it is necessary to start with actual data

from an infrastructure project that is similar to the project in question. This is typically done by

using country-specific Input-Output (IO) tables. This direct employment effect understates, in

some instances significantly, the total employment generated by infrastructure spending. A

survey of the literature6 indicates an actual employment multiplier effects in the range of 1.2 to

3.5.

The availability of non-OECD countries’ IO tables with employment and multiplier data

is limited, restricting the use of this methodology in the case of the countries in the Middle East

and North Africa region. Hybrid methods, such as those pioneered by Schwartz, Andres, and

Dragoiu (2009) and by LECG (2009), can be adapted to address transferability across countries

at different times and stages of development. The hybrid approaches work best in those cases

when economies have similar structures and are at similar levels of development. A study on

Egypt (ILO 2010) provides information from the most recent Egyptian IO table which includes

22 sectors based on ILO data for 2007/08 and the calculation of multipliers for all sectors. This

information is relevant to the oil importing MENA countries whose IO structures are similar to

Egypt’s. However, the GCC and developing oil exporters were judged to be too different in

terms of economic structure and GDP per capita levels to make extrapolation from the Egyptian

case reliable. For this reason we follow Schwartz et al. (2009) and employ an alternative method

for assessing the employment effects of investment spending in MENA.

Schwartz et al. (2009) investigated the employment effects of a stimulus package of

spending in various infrastructure sectors in the Latin America and Caribbean (LAC). They used

project data from a number of World Bank studies to derive the share of investment expenditure

on labor, and the share going to imports, in the main infrastructure sectors. Combining the

expenditure share on labor with data on region-wide average wages (plus benefits) allowed them

to compute the direct employment per US$ billion. The authors used data from the US highway

sector to derive type I and type II multipliers and calculate indirect and induced employment.

Taking a weighted average portfolio of infrastructure sectors allowed them to estimate the

employment created by a representative basket of infrastructure investments.

6 Studies include Tregenna (2007), Bekhet (2011), DIT (2007), SEME (2010), Vesin (2011), Ishihara and Bennett

(2010), and Schwartz et al. (2009).

11

We made a number of extensions and changes to adapt the approach in Schwartz et al.

(2009) for LAC to MENA. First, wage levels were changed to reflect the fact that they are

heterogeneous across and within MENA countries, and different from those in LAC. Following

the idea of Schwartz et al. (2009), hourly wage costs for construction work were estimated for

the three sub-regions of MENA as given in Table 7.7 Computing hourly wages is crucial for all

the estimates and is subject to potential underestimation, specifically for the GCC and the

developing oil exporting countries. To build our reference values, we take data from Gardiner

and Theobald8 (2007) for Lebanon, Qatar and UAE and data from Tong (2010) for the UAE.

9

Those data correspond to the actual cost of labor, as they encompass the various compensation

schemes and not only the direct cash transfers. We need to provide homogenous wage estimates

within sub-regions as the investment needs applied later are aggregated values. To do so, we

compute regional wage averages, based on the ILO Key Indicators of the Labor Market in 2011

and assume constant difference between the ILO indicators and the total compensation in the

selected countries. Our estimates have to be considered carefully as they do not reflect the

intensive use of migrant workers in the infrastructure and construction sectors and the high

variance of wages in developing oil exporters and GCC economies.

Table 7 Estimated hourly wages (in 2010 US$) in infrastructure works

Region US$ per hour:

Qualified workers

US$ per hour:

Non-qualified workers

GCC oil exporters 4.5 3.0

Oil importing countries 1.5 1.0

Developing oil exporters 3.0 2.0

Source: Authors’ estimates

Second, we adopted more conservative multipliers than the estimated multiplier of 4

proposed by Schwartz et al. (2009).10

In this adaptation we use the multipliers for 2007/08 in the

Egyptian IO table. The type II multiplier (the ratio of all jobs created to the number of direct

jobs) varies between 1.09 and 1.82. Those multipliers suggest that the transport and

communication sectors, for instance, have far greater potential to create induced and indirect job

effects than the roads and bridges construction sector. This indicates that when investment

decisions are made with the objective of creating jobs, consideration should be given to both

direct and indirect employment effects as well as the type of skills required to implement

projects.

Third, this adaptation also estimates and accounts for the share of each input factor for

infrastructure projects relevant for MENA countries and based on standard technologies for each

subsector that were not considered in the LAC estimates.11

The shares, presented in Appendix

Table 1, indicate that labor accounts for a much larger share of costs in water and sanitation than

in roads, ports and electricity generation and access. The sanitation sector is most promising as

7 Schwartz et al. (2009) assume hourly wages gross of benefits to be respectively US$6 and US$3 for qualified and

non-qualified workers in LAC. 8 The data in Gardiner and Theobald (2007) for Latin America are consistent with the ones used in Schwartz et al.

(2009), allowing us to use a similar methodology. 9 Converting to US$ hourly wage, the median wage in construction is approximately US$3.7.

10 Such a multiplier implies one indirect job per one direct job, one induced job per one direct and one indirect job.

11 The percentages for railways are adapted from Heintz et al. (2009). The estimates for telecommunication are

adapted from Foreman and Beauvais (1999).

12

an employer of unskilled workers. This sector spends nearly 60% of total costs on nonqualified

workers’ salaries (Annex Table 1). Fourth, this assessment relies on the estimates of investment

needs for infrastructure in the MENA region and its three subregions, presented in Table 5. Thus,

we link the demand for infrastructure with the supply side effects of infrastructure provision on

employment and bring realism into the projections.

Table 8 illustrates our methodology for the oil importing countries. The detailed results

for the two other subregions are provided in Appendix Tables 2 and 3. The direct job per billion

$ in the sector presented in column (1) is obtained by combining the shares of qualified and non-

qualified labor inputs in Appendix Table 1 and the wages in Table 7.12

The share of each sector

in the infrastructure needs of the region in column (2) is taken from Table 5. From (1) and (2) we

derive the number of direct jobs created in each sector by US$ 1 billion of infrastructure

investment (3). We use the type 2 multipliers of the Egyptian IO table (4) to estimate the total

job creation in each subsector (5).

Table 8 Estimated, potential job creation in OIC

Direct job /

billion $ in

the sector (1)

Share of investment

needs (2)

Direct job /

billion $ in

infrastructure

(3)

Type II

multiplier (4)

Total

jobs (5)

Paved Roads 95000 0.24 22353 1.09 24359

Roads 45000 0.10 4538 1.09 4945

Rails 68333 0.02 1148 1.82 2090

Ports 83333 0.02 1401 1.61 2255

Telephone

mainlines 125000 0.03 3782 1.34 5067

Mobile lines 125000 0.10 12395 1.34 16609

Electricity

generation 50000 0.35 17647 1.35 23826

Electricity Access 93333 0.07 6745 1.49 10050

Water 208333 0.03 6653 1.21 8050

Sanitation 226667 0.04 9905 1.21 11985

Total 1.00 86566 109236

Source: Schwartz et al. (2009), Tong (2010), ILO (2011), Foreman and Beauvais (1999), Gardiner and Theobald

(2007), Note 3, Bacon and Kojima (2011) and own computations.

12

Following Schwartz (2009), we consider a yearly average of 2000 hours per worker.

13

The results by country grouping suggest that the infrastructure sector has the potential to

contribute to employment creation in MENA, although it alone will not resolve the region’s

unemployment problem. In the short-run every one billion of US$ invested in infrastructure has

the potential of generating, on average, around 110,000 infrastructure-related jobs in the oil

importing countries, 49,000 jobs in the developing oil exporting countries, and 26,000 jobs in the

GCC economies (Table 9).

The region could therefore generate 2.0 million direct jobs and 2.5 million direct, indirect

and induced infrastructure-related jobs just by meeting estimated, annual investment needs, but

the potential varies greatly across countries,13

and these jobs account for less than 2% of the

labor force in the region. Put differently, these jobs would be foregone if countries decide to trim

their public investment rates going forward. Infrastructure investments could provide a quick

response and be part of the solution to the unemployment challenge, but infrastructure alone will

not resolve this problem.

Table 9 Estimated, potential job creation in response to meeting infrastructure needs in

MENA

Infrastructure

needs

(billions)

Direct

jobs/billion

Total

jobs*/billion

Labor

force

(000) in

2009

Direct

jobs as a

share of

the labor

force

Total jobs

as a share

of the labor

force

GCC 15.8 20859 26194 16387 2.01% 2.53%

OIC 10.3 86566 109236 61598 1.45% 1.83%

OEC 20.7 39454 48573 52884 1.54% 1.90%

Total 46.8 2 037 900** 2 544 457** 130 869 1.56% 1.94%

Source: Authors’ estimates. Notes: *Total jobs include direct, indirect and induced jobs created per billion US$ in the short-run.

**The estimate of total direct jobs in the last row of the table refers to the jobs created by meeting annual infrastructure needs.

This estimate is obtained by multiplying the estimated infrastructure needs for a particular group with the corresponding direct

jobs estimated per US billion, and then summing up across groups.

Long-term employment effects

The long-term employment effect of infrastructure investment in MENA could be

significant. The study finds that the employment response induced by infrastructure investment

resulting in 1% point additional growth is expected to be 9 million additional jobs in the course

of ten years in MENA, or a little less than 1 million jobs per year. Such a response is significant

as it accounts for approximately 30% of the jobs created in the region during the 2000s, and is

based on assessments using employment-growth elasticities from ILO for 2009. Had these jobs

been created during the last decade, the unemployment rate would be substantially lower than the

10% registered in 2009.

The infrastructure investment required to boost growth by 1% point depends on the

output elasticity with respect to infrastructure. The lower the growth elasticity with respect to

infrastructure, the higher the required increase in the stock of infrastructure. In a recent meta-

13

Because of per capita income differences, a given level of spending would generate more jobs in a sector in low-

income Djibouti than in upper middle-income Lebanon, but the latter would find it easier to finance investment

expenditure.

14

analysis of over 100 studies, Estache and Garsous (2011) find that the effect of infrastructure on

growth depends on three main factors: (i) the specific indicators used to approximate

infrastructure;14

(ii) the time period analyzed;15

and (iii) the level of development of the country

in question.16

Since there are no specific growth elasticities with respect to infrastructure for the MENA

region or countries, it is necessary to rely on a survey of international experience in developing

countries to obtain an estimate of the output elasticity with respect to infrastructure. Although

there is quite a large literature on the topic, relatively few studies cover developing countries.

The basic average elasticity used for the MENA sample, and an associated confidence interval,

draw on the estimation results from ten studies focusing on developing countries presented in

Table 10. These are relatively high elasticities when compared to those used for developed

countries – a fact consistent with one of the lessons in Estache and Garsous (2011). The variance

is however large enough to be concerned about the reliability of the average elasticity derived

from this sample.

Table 10 Output elasticities with respect to infrastructure for developing countries

Authors Estimated Elasticity

Dessus & Herrera (2000) 0.13

Gwartney, Helcombe & Lawson (2006) 0.17

Khan & Kumar (1997) (Africa) 0.32

Khan & Kumar (1997) (Asia) 0.26

Nazmi & Ramirez (1997) 0.129

Odedokun(1997) 0.033

Ram(1986) 0.372

Ram(1996) 0.299

Ramirez (1998) 0.58

Sanchez-Robles (1998) 0.003

Sridhar & Sridhar (2004) 0.098

To assess the robustness of the elasticity, we build a confidence interval for the mean μ of

this sample. The empirical mean and the standard error of this sample are respectively given by

=0.22 and s=0.17. Therefore, assuming normality, we have:

.

Consequently, there is only a 5% chance that μ does not fall into the following interval:

.

14

Using energy as a proxy guarantees a much stronger impact than using water or even telecoms, and a synthetic

indicator provides an intermediate level of impact as expected. 15

The impact was stronger in the 1950s and 1960s than in the last two decades. 16

The less developed the country, the higher the likely impact. However, this result is not as statistically robust as

expected.

15

The boundaries of this interval define reasonably robust lower and upper bounds for the output

elasticity with respect to infrastructure in developing countries. The lower bound of the elasticity

suggests that an increase of 8.7% in the stock of infrastructure is required to add a percentage

point to growth in the MENA region. This is the more likely scenario in high-income MENA,

comprised of the GCC economies and some upper middle-income MENA countries, since the

growth impact of an additional unit of infrastructure investment tends to be smaller in the more

developed countries. With the upper bound elasticity, the required increase in infrastructure stock

is just 3.1%.

6. Policy implications and concluding remarks

Infrastructure investment has the potential to create jobs quickly, while providing a foundation

for future growth. This is especially important in the oil importing countries, where the

infrastructure gap is large and employment needs are growing. However, it is also likely to be

most difficult in these countries because of strained finances. Going forward, government

decisions on what types of spending to expand and what to downsize in order to achieve

balanced budgets will have important implications for jobs. In designing country specific

solutions, governments will have to take on predictable challenges: the governance of job

creation, the proper targeting and fiscal costs assessment of subsidies needed to create jobs, the

design and fiscal costs of the (re)training programs needed and the expectations on the job

creation effects of infrastructure.

The governance challenge

Prudent infrastructure development will be critical for short and long term growth and job

creation because the greatest risk to using infrastructure as part of an employment and growth

strategy in MENA countries is poor governance. A recent report on investment in MENA (World

Bank, 2011) shows that in economies with weak rule of law there is no evidence that public

investment stimulates private investment and growth. In contrast, in countries with an adequate

level of property rights protection, accountability and legal institutions, public investment is

strongly linked to growth. In addition, good rule of law helps attract private investment and

countries with good rule of law show higher levels of investment efficiency.

Not all jobs are equal in terms of skills and not all infrastructure investments are equal in

terms of ability to create jobs of different skills. This means that investments in infrastructure

will need to be prioritized based on the employment and infrastructure needs and opportunities of

the country. For example, road and bridge construction projects will have direct impact on

creation of relatively low-skilled jobs. These types of projects will be especially effective in

addressing job-related concerns in countries where there is a large pool of relatively unskilled

and unemployed nationals. This is the case in most MENA countries where the majority of the

unemployed do not have tertiary education. By contrast, projects in transport and communication

services have large indirect effects, and therefore the ability to create a diverse set of jobs for

workers with different skill levels. These projects will appeal to policy makers in countries

where the unemployed have the ability to acquire specialized skills relatively quickly.

16

The subsidy targeting challenge

Public works and different types of subsidized employment programs have been used

widely to make it easier for people who cannot find unsubsidized jobs to find employment and

acquire on the job skills. These programs are necessary, for instance, to address structural issues

which will not be addressed through market forces alone as economies grow bigger and can be

particularly effective when dealing with unemployment issues in a regional context. Subsidies to

job creation in infrastructure and construction will have to be designed to make the most of

employment opportunities for low-skilled workers. The design of the targeting will also have to

address the pressing nature of the need to create job. Indeed, boosting short-term job creation in

developing MENA is desirable, particularly in the context of recent political developments. But

subsidized employment programs are costly and should be designed to ensure a positive spillover

to long-run employment and employability.

Different types of job subsidy targeting strategies involve different types of

implementation and monitoring costs as well as different degrees of effectiveness (Amin et al.,

2008). There are relatively easy solutions to minimizing these costs but they take time to put in

place. In MENA, vouchers may be considered to minimize the costs of targeting as they are more

efficient than direct subsidies, and targeting the long-term unemployed is more efficient than the

less qualified (Brown et al. 2011).

The design of targeting practices is essential to the effectiveness of the program. When

targeting is not direct, firms will potentially select beneficiaries that would have been more likely

to find a job without the transfer policy (Marx 2001). This increases the risk of deadweight loss

through substitution effects. There is also a risk that, if the measures have not been designed to

target a sufficiently large range of potential beneficiaries, some employers will not take the time

and energy to use them. Finally, the real risk is that only large and public firms will benefit from

these programs because these firms have the capacity to mobilize the resources needed to capture

the subsidies. There is thus a tradeoff between the fact that generous measures generate a greater

response but also a greater burden.17

A way to avoid the risks and costs of direct targeting is to design subsidies such that

workers self-select for the subsidized jobs. The objective of self-targeting policies is to ensure

that certain categories of workers, the poor or women for instance, self-select into the subsidized

jobs, while the non-targeted groups choose regular jobs. The subsidies must therefore be such

that targeted workers are willing to accept the job (participation constraint) and do not have a

better job opportunity (incentive compatibility). Similarly, incentive compatibility must be such

that non-targeted groups refuse the subsidized jobs. However, if the resulting wage is too low,

this self-targeting subsidy can tend precisely to emphasize the wage gaps and stigmatize a

category of workers (Devereux and Solomon, 2006).

The employment subsidies costing and financing challenge

The net costs of subsidizing job creation are difficult to estimate, although the temporary

nature of the subsidies, which last only during the investment phase of an infrastructure project,

17

We assume that: (i) equal incremental increases in taxes lead to progressively larger welfare losses; and (ii) equal

incremental increases in each employment subsidy leads to progressively smaller incremental increases in

employment and social welfare, and a progressively larger government budgetary outlay (Brown et al. 2011).

17

minimizes any potential losses. In addition to the direct fiscal costs of providing the subsidies

and any associated training and program management, there are less obvious costs in the form of

deadweight loss, substitution and displacement effects. The costs would also be overestimated if

the induced formalization of the labor market and hence the potential revenue from labor taxes

are ignored, and underestimated if this formalization leads fast to added expenses in

unemployment benefits and other indirect related costs. There is also the opportunity cost of how

the funds are spent. In an economy with poor institutional quality and high levels of rent-seeking

behavior public spending on infrastructure could lead to projects with low value added and cost

overruns. Thus, good governance is a key complement to infrastructure spending.

When considering the option of subsidizing the creation of jobs, governments invariably

face the challenge of determining the optimal duration of subsidizing infrastructure. In case of a

temporary economic downturn, short-term wage subsidies are a good option to avoid hysteresis.

A short term policy of wage subsidies increases the probability that the beneficiaries will be

employed (Bell and Orr, 1994; Betcherman et al., 2010; Forslund et al., 2004; Kangasharju,

2007; Katz, 1996; Marx, 2001; Sianesi, 2002).

In poor countries infrastructure subsidies bring an additional concern arising from the

potentially perverse incentive that entices people away from agricultural jobs. A way to

minimize such a risk could be to support infrastructure in the off-season for farming. But the

impact of short-term infrastructure subsidies could also lead to competition for workers from

other sectors and an upward pressure on wages, with potentially negative consequences for

competitiveness. The poverty reduction impact of such higher wages is also questionable, as they

may not translate into higher purchasing power because the prices of key goods and services

consumed by the poor could increase as well. Targeting of short-term, relatively specialized,

infrastructure jobs may reduce substitution effects. However, if the wage elasticity is lower in the

sector, total job creation from a given short term budget may end up being lower than hoped for

(Bucher, 2010; Gerfin et al., 2005; Sianesi, 2002).

Long-term subsidized programs are typically considered in response to mass lay-offs

from a major economic restructuring. The main challenge in these cases is to avoid sustaining

sectors or activities which have no prospects for future development (ILO/IMF, 2011). In the

case of infrastructure, subsidized work programs can contribute two types of jobs – (i) those that

support the investment components of the sector (known as CAPEX) in the short term and (ii)

longer lasting jobs created to operate and maintain the long lived assets (these expenditure are

known as OPEX) in the industry.

When committing to support jobs over a longer period of time, the risk of generating

perverse incentives would potentially increase as there might be a sense that subsidies would be

permanent. One such perverse incentive is the effect that long-term wage subsidies have on

displacement costs, i.e. job losses in non-subsidized firms through distortion of competition

(Marx, 2001). Also, if job subsidies permit people to keep rights to generous unemployment

benefits, people might switch from relying on benefits to relying on subsidized jobs instead of

entering the labor market (Sianesi, 2002), and some categories of workers might be locked in

temporary and subsidized jobs (Van Ours, 2004).

There are some positive aspects too. Subsidies can compensate for the implicit tax on

severance imposed by employment protection and avoid displacement costs if the value of the

subsidy is higher than severance costs (Mortensen and Pissarides 2003, Galasso et al. 2004).

18

Experience from Finland shows that no displacement costs were observed because subsidized

jobs had to be new, and only one-third of the wage was being subsidized (Kangasharju 2007).

Finally, it is important to keep in mind that long term programs can be seen as a redistribution

device (Brown et al. 2011), but that the odds of generating a lot of perverse incentives in the

process are quite high.

In sum, short-term subsidized work programs can be used more efficiently than long-term

programs to facilitate inclusion in the labor market. Wage subsidies in infrastructure works can

be designed to limit perverse incentives but the design requires a serious diagnostic of the local

labor market characteristics.

The training challenge

Experience shows that the long term payoffs of employment subsidies can be achieved

only if subsidized employment programs are combined with training and counseling. Therefore,

the design of these programs should be given as much attention as the design of the subsidized

employment programs. Specific training should be considered only if there is market demand for

these qualifications or if there is a need to buy time in a labor market restructuring transition.

Often general training supporting labor market flexibility will be sufficient and more efficient in

increasing productivity than specialized training. Data from Ireland confirms that general

training raises productivity, but the same cannot be said about specialized training (Estache et al.

2000).

In theory, workers are more likely to acquire general training when markets are

competitive and the turnover is high (Wasmer 2006). However, subsidized jobs for low-skilled

workers may reduce incentives to become skilled – an effect amplified by the fact that taxes used

to pay for subsidies may result in an additional tax burden for skilled workers (Oskamp and

Snower 2006). There is also no reason to provide training specific to the infrastructure sector if

the subsidized job is temporary and the objective of the training is to facilitate inclusion into the

general labor market, and not in the infrastructure sector.

The challenge of managing expectations

The study shows that infrastructure investments could provide a relatively quick short

term response to MENA’s unemployment challenge. As such, it is part of the solution, but

infrastructure alone will not resolve the problem. Infrastructure and construction jobs represent

less than 20% of the jobs in most countries of the region. Even a dramatic increase in labor

intensive infrastructure investments and maintenance would not be able to address the very large

unemployment rate of the region. Countries should press on with reforms that improve the

business environment, and especially, business regulations and governance. The importance of a

sound regulatory environment and good governance for inclusive growth has been underscored

in numerous studies. This particular one focused on estimating the employment impact of

infrastructure investment in MENA. In the future, more work needs to be done to assess the

impact of infrastructure investment on different types of labor, e.g. skilled vs. unskilled, young

vs. old and domestic vs. migrant workers. The latter is particularly important because if unskilled

positions are largely filled with migrant workers, the job creation effects of infrastructure

investment may result in increased immigration, not lower unemployment.

19

The following caveats should also be kept in mind. The estimations assume that wages

are fixed. This is not unrealistic given that only very large infrastructure projects relative to the

size of the economy could impact the level of wages. Still, large investment projects could have

an impact on wages, implying that the lower bound for the marginal impact of US$ 1 billion

investment may be an overestimate of the employment impact. The estimates do not consider

several types of costs that could reduce the job creation effect, including the cost to the private

sector due to labor substitution effects, opportunity cost of capital, costs due to crowding out,

environmental costs, and cost related to governance issues. Last but not least, the possibility of

leakages from imports of goods and services associated with infrastructure investment is serious

but hard to estimate.

20

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23

Appendix Table 1

Estimated shares of inputs in different types of infrastructure

Qualified

workers

Non

qualified

workers

Domestic

material

inputs

Imported

inputs

Other

inputs

Paved Roads 0.15 0.06 0.49 0.16 0.14

Roads 0.03 0.09 0.22 0.63 0.03

Rails 0.13 0.01 0.52 0.24 0.10

Ports 0.10 0.10 0.80

Telephone mainlines 0.15 0.15 0.30 0.24 0.16

Mobile lines 0.15 0.15 0.30 0.24 0.16

Electricity generation 0.10 0.90

Electricity Access 0.14 0.07 0.26 0.53

Water 0.25 0.25 0.40 0.10

Sanitation 0.08 0.56 0.32 0.04

Source: Schwartz et al. (2009) and authors’ estimates.

24

Appendix Table 2

Job creation potential in the GCC countries

Direct job /

billion $ in the

sector (1)

Share of

investment

needs (2)

Direct job / billion $

in infrastructure (3)

Type II

multiplier (4)

Total

jobs (5)

Paved Roads 31667 0.12 3800 1.09 4141

Roads 15000 0.28 4200 1.09 4577

Rails 22778 0.00 0 1.82 0

Ports 27778 0.04 1111 1.61 1789

Telephone

mainlines 41667 0.01 333 1.34 447

Mobile lines 41667 0.04 1500 1.34 2010

Electricity

generation 16667 0.48 8067 1.35 10891

Electricity

Access 31111 0.01 373 1.49 556

Water 69444 0.01 417 1.21 504

Sanitation 75556 0.01 1058 1.21 1280

Total 1.00 20859 26194

Source: Schwartz et al. (2009), Tong (2010), ILO (2011), Foreman and Beauvais (1999), Gardiner and Theobald

(2007), Note 3, Bacon and Kojima (2011) and own computations.

25

Appendix Table 3

Job creation potential in the Developing Oil Exporting Countries

Direct job /

billion $ in the

sector (1)

Share of

investment

needs (2)

Direct job / billion $

in infrastructure (3)

Type II

multiplier (4)

Total

jobs (5)

Paved Roads 47500 0.25 11952 1.09 13025

Roads 22500 0.20 4404 1.09 4799

Rails 34167 0.01 318 1.82 579

Ports 41667 0.00 0 1.61 0

Telephone

mainlines 62500 0.03 1922 1.34 2576

Mobile lines 62500 0.07 4310 1.34 5776

Electricity

generation 25000 0.35 8644 1.35 11670

Electricity

Access 46667 0.04 2088 1.49 3110

Water 104167 0.02 2330 1.21 2819

Sanitation 113333 0.03 3486 1.21 4218

Total 1.00 39454 48573

Source: Schwartz et al. (2009), Tong (2010), ILO (2011), Foreman and Beauvais (1999), Gardiner and Theobald

(2007), Note 3, Bacon and Kojima (2011) and own computations.

26

Annex

Data sources and description used for model of investment requirements

GDP in constant 2000 USD is taken from the World Development Indicators (WDI) of the

World Bank (http://data.worldbank.org/) and UN National Accounts Main Aggregates

Database (http://unstats.un.org/unsd/snaama/selbasicFast.asp). GDP projections for all MENA

countries except for West Bank and Gaza come from The World Bank Growth Forecasting

Tool described in Ianchovichina and Kacker (2005).

Shares of value added in agriculture and manufacturing come from the WDI database of The

World Bank (http://data.worldbank.org/) and UN National Accounts Main Aggregates

Database (http://unstats.un.org/unsd/snaama/selbasicFast.asp).

Total and urban population data are taken from the WDI database of The World Bank

(http://data.worldbank.org/). Projections are obtained from the United Nations World

Urbanization Prospects (2009 Revision). (http://esa.un.org/unpd/wup/index.htm)

Containerization, measured as the total number of trafficking containers, is obtained from the

World Development Indicators (WDI) of the World Bank (http://data.worldbank.org/) and

harmonized with the Containerization International Yearbook (1970-2006), published by

Containerization International (http://www.ci-online.co.uk).

Telephone lines, mobile phones (in subscribers per 1000 inhabitants), paved and total roads,

and rails (in thousands of kilometers), come from the WDI database of The World Bank

(http://data.worldbank.org/)

Electricity generating capacity, in millions of kilowatts, is taken from the US Energy

Information Administration,

(http://tonto.eia.doe.gov/cfapps/ipdbproject/IEDIndex3.cfm?tid=2&pid=2&aid=12).

Electrification rate, measured as the fraction of population with access to electricity, is

obtained from World Energy Outlook 2006, 2009 and 2010 published by the International

Energy Agency (http://www.worldenergyoutlook.org/).

Access to improved water and sanitation in urban and rural areas is defined as the fraction of

total population with access to these services. It is taken from the WDI database of The

World Bank (http://data.worldbank.org/)

Waste water treatment, measured as the fraction of the population connected to public waste

water treatment plants, is obtained from the United Nations Statistical Division

(http://unstats.un.org/unsd/environment/wastewater.htm)

Kilometers of total and paved roads and port traffic in tons for Oman are obtained from the

Ministry of National Economy (http://www.moneoman.gov.om/Stat_Online_desp.aspx).

Electrification rate for Djibouti is taken from the Energy Survey carried out by the

Government and the World Bank. (http://www.ministere-finances.dj/statistiques/Projets/rapportfinalenergie.pdf)